1. Field of the Invention
The present invention relates to an image processing apparatus and an image processing method, and more particularly, to an image processing apparatus and an image processing method that perform noise reduction processing on an image signal.
2. Description of Related Art
Generally, an image pickup apparatus provided with an image pickup device such as a CCD or CMOS photoelectrically converts an image optically formed on an image pickup plane via lenses in micro regions pixel by pixel and thereby outputs an image signal as an electric signal. Furthermore, the aforementioned image signal is amplified by an amplifier to a predetermined brightness level, digitized by an A/D converter and subjected to further processing as a digital image.
Various types of noise ascribable to the image pickup device are mixed into the digital image digitized as described above. Examples of the above described noise include dark current, fixed pattern noise caused by a variation in gain of the amplifier accompanying a variation of each pixel and random noise as shot noise caused by statistical nature at the time of photoelectric conversion. Furthermore, the statistical characteristic of the aforementioned noise is known to vary with the brightness level. Shot noise in particular has average amplitude proportional to the square root of the brightness level.
On the other hand, for example, processing by a spatial smoothing filter using spatial correlativity of the image signal and spatial non-correlativity of noise is widely known as processing that reduces the noise level of a digital image into which noise originating in the image pickup device is mixed and can thereby improve an SN ratio. However, the spatial smoothing filter often has an adverse effect on an edge section of the image. Therefore, Japanese Patent Application Laid-Open Publication No. 2006-302023 describes a noise reduction method using such an edge-preserving filter that a weighting factor of a smoothing filter adaptively varies between an edge section and parts other than the edge section of the image.
The noise reduction filter according to Japanese Patent Application Laid-Open Publication No. 2006-302023 is a filter that adaptively changes weights according to a difference in pixel values between a target pixel to be processed within a target region and a pixel peripheral thereto. To be more specific, the noise reduction filter according to Japanese Patent Application Laid-Open Publication No. 2006-302023 reduces the weight to 0 when the absolute value of the aforementioned difference value is above a threshold SH, and is configured on the other hand, when the absolute value of the aforementioned difference value is equal to or below the threshold SH, using a filter coefficient whereby the absolute value of the difference value is converted to a weight using a function that monotonously decreases down to a predetermined value as the absolute value of the aforementioned difference value increases from 0 and monotonously increases when the absolute value of the aforementioned difference value reaches or exceeds the predetermined value. Using such a filter designed based on the difference value between the target pixel and the pixel peripheral thereto makes it possible to suppress noise in a flat part while preserving the edge section of the image.
Furthermore, as the adaptive smoothing filter, the weight of which adaptively varies according to the structure of an image, there are, for example, filters called a “rational filter” and a “bilateral filter” expressed by following equation (1).F(x,y)=N·exp{−(|spatial distance(x,y)/σs)2/2}·exp{−(|pixel value difference(x,y)/σd)2/2}  (1)
As shown in equation (1) above, the bilateral filter has a filter coefficient obtained by multiplying a Gaussian filter corresponding to a spatial distance by a Gaussian filter corresponding to a pixel value difference. The first term of the right side of equation (1) above indicates that a fixed weight independent of the structure of an image is given and the second term of the right side in equation (1) above indicates that a weight that adaptively varies depending on the structure of the image is given.
The bilateral filter expressed by equation (1) above operates so as to exclude pixels having a large difference in pixel values between the pixel to be processed and a pixel peripheral thereto from smoothing processing as much as possible, and therefore never blunts edge sections having large differences in pixel value. As a result, the bilateral filter expressed by equation (1) above can reduce a large amount of noise while maintaining resolution, and can thereby obtain an effective noise reduction result.
The second term of the right side of equation (1) above indicates that the difference in pixel values used for smoothing is a difference on the order of σd at most. When the value of this σd is fixed, a selection criterion of pixels used for smoothing becomes constant within the image. However, the amount of noise originating in the image pickup device varies depending on the brightness level as described above. Therefore, fixing value of σd is inconvenient when the processing is actually performed. In consideration of such circumstances, a technique of changing the value of σd of the second term of the right side according to the amount of noise generated in the bilateral filter expressed as equation (1) above is described in U.S. Patent Application Publication No. 2007/0009175.
U.S. Patent Application Publication No. 2007/0009175 describes a technique of storing a standard deviation value, which is an amount of noise determined according to the brightness level and measured beforehand as a table, outputting an amount of estimated noise with respect to the brightness level of the pixel to be processed and causing the value of σd to correspond to the amount of estimated noise. According to such a technique described in U.S. Patent Application Publication No. 2007/0009175, it is possible to design a filter weight adaptable not only to a spatial structure of an image but also to the brightness level, and thereby obtain an effective noise reduction result without crushing even a smaller edge structure.
On the other hand, a rational filter expressed as equation (2) below does not crush the micro structure so much as the aforementioned bilateral filter.F(x,y)=T/(|pixel value difference|+T)  (2)
In the case of the rational filter expressed as equation (2) above, T is the parameter that corresponds to σd above.